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The structure and evolution of immunoglobulin repertoires

English title The structure and evolution of immunoglobulin repertoires
Applicant Reddy Sai
Number 170110
Funding scheme Project funding (Div. I-III)
Research institution Computational Systems Biology Department of Biosystems, D-BSSE ETH Zürich
Institution of higher education ETH Zurich - ETHZ
Main discipline Immunology, Immunopathology
Start/End 01.01.2017 - 31.12.2019
Approved amount 530'028.00
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All Disciplines (2)

Discipline
Immunology, Immunopathology
Molecular Biology

Keywords (4)

high-throughput; B cells; bioinformatic; antibody repertoire

Lay Summary (German)

Lead
The structure and evolution of immunoglobulin repertoires
Lay summary
Dieser Vorschlag beschreibt die Entwicklung einer Methode zur Bewertung von Immunglobulinrepertoires hinsichtlich der klonalen Konvergenz, Expansion, Evolution und Diversität. Diese Methode wird dann angewendet, um grundlegende Fragen im Zusammenhang mit B-Zell-Entwicklung und Differenzierung nach Immunisierung in Mäusen zu beantworten. Die Ergebnisse dieses Projekts werden das aufkeimende Feld der Systemimmunologie weiter ausbauen und zukünftige Anwendungen in der Biotechnologie und Medizin ermöglichen.
Direct link to Lay Summary Last update: 22.12.2016

Responsible applicant and co-applicants

Employees

Publications

Publication
Large-scale network analysis reveals the sequence space architecture of antibody repertoires
Miho Enkelejda, Roškar Rok, Greiff Victor, Reddy Sai T. (2019), Large-scale network analysis reveals the sequence space architecture of antibody repertoires, in Nature Communications, 10(1), 1321-1321.
immuneSIM: tunable multi-feature simulation of B- and T-cell receptor repertoires for immunoinformatics benchmarking
(2019), immuneSIM: tunable multi-feature simulation of B- and T-cell receptor repertoires for immunoinformatics benchmarking, in bioRxiv, 759795.
Comparison of methods for phylogenetic B-cell lineage inference using time-resolved antibody repertoire simulations (AbSim)
Yermanos Alexander, Greiff Victor, Krautler Nike Julia, Menzel Ulrike, Dounas Andreas, Miho Enkelejda, Oxenius Annette, Stadler Tanja, Reddy Sai T (2017), Comparison of methods for phylogenetic B-cell lineage inference using time-resolved antibody repertoire simulations (AbSim), in Bioinformatics, 33(24), 3938-3946.

Associated projects

Number Title Start Funding scheme
143869 Quantitative molecular analysis of polyclonal memory B cell responses 01.06.2013 Project funding (Div. I-III)
197941 Single-cell profiling of antibody repertoires and transcriptomes from B cells to determine the relationship with antigen-specificity and aging 01.11.2020 Project funding (Div. I-III)

Abstract

Humoral immunity is dependent on the immunoglobulin repertoire, which is a vast ensemble of molecularly distinct B cell receptor (BCR) and antibody clonal variants. The immunoglobulin repertoire of an individual reflects their current immunological status and past exposure to pathogens. The recent progress in high-throughput sequencing of immunoglobulin repertoires (Ig-seq) has catalyzed a big-data driven revolution in adaptive immunity. Ig-seq has formed an integral part of the burgeoning field of systems immunology, which offers an opportunity to further describe and understand the complexity of the immune system. It is now possible through Ig-seq to acquire a plethora of quantitative molecular information on the central principles of humoral immunity such as clonal selection and expansion, diversity, and somatic hypermutation. Although Ig-seq is still a very new method, it has already been utilized to answer several basic questions and for applications in biotechnology and medicine. In previous work, our lab has established a variety of experimental and bioinformatic tools for Ig-seq, such as advanced library preparation, replicate sequencing analysis, error and bias correction. To address an immunological question, we have also used Ig-seq to determine the balance of nature, nurture, and noise on immunoglobulin repertoires, leading to the novel discovery that intrinsic VDJ recombination bias results in convergent repertoires in different individuals (mice). One of the next steps in systems immunology and Ig-seq is to study the underlying emergent properties of immunoglobulin repertoires through the use of network theory, as this may lead to the discovery of the status and evolution of specific immune responses. The overall goal of this research proposal is to develop and apply a network theory methodology for studying humoral immune responses. Specifically, we will quantify the structure and evolution of immunoglobulin repertoires through B cell development and following immunization. A major challenge in Ig-seq is the fact that many of the existing analytical tools require disparate statistical and bioinformatic approaches, which leads to a lack of data integration and the inability to make meaningful immunological interpretations. In Aim 1, we will first develop the infrastructure to perform large-scale network analysis of immunoglobulin repertoires, which consists of applying a high-performance computing platform to determine the global structure of immunoglobulin networks. The advantage of Ig network analysis is that it will describe in detail the network layout and structure of immunoglobulin repertoires, which is highly valuable as both the sequence diversity and frequency architecture of immunoglobulin repertoires determine to a very large extent the specificity of antibody responses. In Aim 2, we will establish a bioinformatic and statistical framework to mine and translate the local properties of immunoglobulin repertoire networks. Finally, in Aim 3, will apply the methods established to reveal the underlying architecture of immunoglobulin repertoire networks on Ig-seq data obtained from mice. Ultimately, we will provide for the first time a network view of B cell clonal selection and expansion. The results of our proposal will also set the stage for future use of Ig-network analysis for applications in biotechnology and medicine such as antibody engineering, immunodiagnostics, and vaccine design.
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